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IBM Cognos Data Manager: Build Data Marts with Enterprise Data (V10.2) is a five-day, instructor-led course that teaches participants how to move, merge, consolidate, and transform data from a range of data sources to build and maintain subject-area data marts. In the process, students will create a catalog and add connections to data sources and targets. They will also deliver fact and dimension data to a data mart through the use of builds and the dimensional framework. In addition, students will learn how to automate common functionality and handle complex data issues, such as unbalanced hierarchical structures.

Please refer to course overview for description information.

This course is intended for Developers.

You should have:

a knowledge of basic Windows functionality, database and dimensional analysis concepts, as well as a working knowledge of SQL

Getting Started

Identify the purpose of IBM Cognos Data Manager

Define data warehousing and its key underlying concepts

Identify how Data Manager creates data warehouses

Examine the Data Manager architecture and user interface

Create a Catalog

Examine the purpose and contents of Data Manager catalogs

Create a catalog

Define connections to source and target data

Access data using SQLTerm

Configure flat data source files using SQLTXT

Create Hierarchies

Examine the role of the dimensional framework in Data Manager

Examine hierarchies and their data sources

Identify how to create hierarchies from the columns of one table, the rows of one table, and from multiple tables

Test and view hierarchies

Create a hierarchy of static date values

Handle weeks in a date hierarchy

Create Basic Builds

Examine Data Manager builds and build-related terminology

Create a dimension build using the Dimension Build wizard

Create a fact build using the Fact Build wizard

Test and execute a fact build

Document a catalog

Create catalog schema

Create Derivations

Examine derivations

Apply operators and functions to derivations

Examine the derivation timing model

Add derivations to a fact build

Create Conformed Dimensions

Examine conformed dimensions and their advantages

Design conformed dimensions

Create conformed dimensions

Create data integrity lookups that use conformed dimensions

Customize Reference Structures

Create hierarchies manually using different approaches

Examine the features of a hierarchy

Examine literals

Set data access for hierarchy levels

Examine static and dynamic members

Examine fostering

Use derivations in a hierarchy

Process Dimensional History and Late Arriving Facts

Examine slowly changing dimensions (SCDs)

Use surrogate keys in SCDs

Manage type 1 and type 2 changes to dimensional data

Load historical data for a dimension

Examine late arriving facts

Process late arriving facts in a fact build

Transform Data Using Lookups and Derived Dimensions

Identify when to use lookups

Identify the requirements for a lookup

Create a translation lookup

Create an optional lookup

Add derived dimensions to fact builds

Customize Data Delivery

Configure fact and dimension delivery modules

Create indexes on fact and dimension tables

Update fact data using keys

Customize Fact Data Processing

Filter fact data

Merge duplicate fact data

Examine fact data integrity checking

Reject fact data

Aggregate, Filter, and Partition Fact Data

Aggregate fact data

Examine aggregate rules

Vertically restrict fact data

Horizontally restrict fact data

Partition fact data

Implement Job Control

Examine where job control fits into the data warehouse lifecycle

Create a JobStream

Add, link, and reposition nodes

Execute a JobStream and view the results

Automate Functionality Using Commands

Differentiate between the Command Line Interface (CLI) and Data Manager Designer

Identify common commands

Use commands in a batch file

Examine variables

Customize Functionality with User-Defined Functions and Variables

Examine user defined functions (UDFs)

Create an internal UDF

Create a user-defined variable

Process Unbalanced Hierarchical Data

Examine balanced, unbalanced, and ragged hierarchies

Add a recursive level to a hierarchy

Identify ways to balance a hierarchy and delivered flattened data

Examine circular references

Pivot Fact Data

Examine pivoting

Use the single pivot technique

Use the advanced pivot technique

Examine reverse pivoting

Resolve Data Quality Issues

Identify data quality and cleansing issues

Handle fostered and unmatched members

Perform debugging using SQLTerm and functions

Assess the quality of output data

Troubleshoot and Tune the Data Manager Environment

Use build logging to ensure that data marts are being loaded properly

Perform dimension breaking

Manage memory and resources

Export DDL statements

Organize and Package Data Manager Components

Export and import components using packages

Search for components in a catalog using Navigator

Integrate with IBM Cognos BI

Examine IBM Cognos BI

Identify the role of metadata dimensions, metadata collections, and metadata stars